Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems

Understand

Large language model-based multi-agent systems have recently gained significant attention due to their potential for complex, collaborative, and intelligent problem-solving capabilities.

• Existing surveys typically categorize LLM-based multi-agent systems (LLM-MAS) according to their application domains or architectures, overlooking the central role of communication in coordinating agent behaviors and interactions.
• To address this gap, this paper presents a comprehensive survey of LLM-MAS from a communication-centric perspective.
• Specifically, we propose a structured framework that integrates system-level communication (architecture, goals, and protocols) with system internal communication (strategies, paradigms, objects, and content), enabling a detailed exploration of how agents interact, negotiate, and achieve collective intelligence.